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arXiv · 2606.13544

Adaptive Turn-Taking for Real-time Multi-Party Voice Agents

Soumyajit Mitra·Prabhat Pandey·Abhinav Jain·Shanmukha Sahith·K V Vijay Girish
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Abstract

Turn-taking in multi-party spoken conversations remains a fundamental challenge for voice-based agents, particularly under dynamic floor competition and varying user expectations. We propose ModeratorLM, a role-playing voice agent that conditions turn-taking behavior on an explicitly assigned role in multi-party settings. The system is built on a speech large language model operating in chunk-wise streaming manner. We further introduce a reasoning-augmented variant that incorporates chain-of-thought reasoning over conversational context and the assigned role. We construct RolePlayConv, a large-scale synthetic dataset of spoken multi-party conversations with diverse assistant roles. Experiments on real-world meeting data and RolePlayConv show improved turn-taking precision by over 40% and recall by more than 70%, while substantially reducing false-positive interruptions compared to non-role-conditioned baselines.

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Soumyajit Mitra, Prabhat Pandey, Abhinav Jain, Shanmukha Sahith, K V Vijay Girish. 2026-06-11. Adaptive Turn-Taking for Real-time Multi-Party Voice Agents. https://arxiv.org/abs/2606.13544

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